Classification of distinct conformers of beta-2 adrenergic receptor based on binding affinity of ligands through docking studies

Abstract

?2AR is an important drug target and plays a critical role in the relaxation of pulmonary tissues and cardiovascular physiology. We have developed a strategy for classifying various ?2AR conformers as active or inactive states based on binding mode of selected ligands with known activities. Previously distinct conformational states of the ligand’s binding pocket were obtained from a 2.8 µs MD simulation. Snapshots were clustered based on RMSD value of five key residues at the binding site. Clustering analysis yielded a total of 13 distinct conformers to which five agonists four inverse agonists and four antagonists were docked separately using seven different scoring functions. Best ligand poses with the highest score value were selected and evaluated based on their vicinity to five key residues. Poses that were not in this neighborhood were discarded and remaining ones were sorted based on their score. Before treating MD conformers this classification scheme was applied first to both active/inactive state crystal structures for critical assessment. MD conformers found in top five in all scoring functions were selected and assigned to be either active or inactive. Finally selected MD conformers were used to screen a small database to further investigate their discriminatory power. As a result MD conformers performed more selective screening than inactive state crystal structure for antagonists/inverse agonists. Generating alternative conformations of the receptor and classifying them as active or inactive is an important practice in the drug design studies that were often limited to one snapshot obtained from X-ray studies.